In video coding, a compression process typically involves a residual filter for spatial filtering and a temporal prediction filter. The residual filter may use a discrete cosine transform (DCT), wavelet, or a lifting transform. The temporal prediction filter allows a target image to be predicted from a set of reference images (usually 1 or 2). The temporal prediction filter uses a set of motion vectors that represent an object that has changed position in the target image relative to the reference images (i.e., moved) and a filter that operates over the motion vector data. Standard approaches to temporal prediction use a regular or uniform pattern of motion vectors to perform simple motion compensation for each block represented by the motion vector.
There is a trend toward using an irregular motion vector pattern in the target image. An irregular pattern of motion vectors arises from adapting the motion vector positions in the target image (e.g., more motion vectors near moving object boundaries, fewer in background regions) in order to improve the temporal prediction. Generating the irregular motion vector pattern is often a highly complex procedure, however, and is typically performed on the target image without regard to the effects of spatial-temporal filtering. This process is not desirable as there may significant overlap between the effects of spatial-temporal filtering and irregular motion vector sampling.
For example, certain regions of the image, even though they may have complex motion, may be very easily filtered because the spatial correlation is very high. Hence, these regions do not require an irregular distribution of motion vectors. Because a simple, uniform pattern of motion vectors can be used to avoid the complexity cost of generating the irregular motion vector pattern. Conventional approaches are unable to link the generation of an irregular motion vector pattern with the results of spatial-temporal filtering.